Right from the start in 2020, the Research Data Services (RDS) at the University Duisburg-Essen designed its services for research data management (RDM) with the intention of addressing both generic needs of all researchers and discipline-specific requirements of research networks. The challenge lay in identifying general, overarching needs while simultaneously considering the possibilities for individual customization. To achieve this balance, RDS have established an interlinking concept that integrates central services and infrastructure projects (INF) across three Collaborative Research Centers (CRCs): CRC/TRR 196 MARIE, CRC/TRR 296 LOCOTACT, and CRC 1430. The interlinking concept allows for the creation of individual research data management workflows, tailored to the discipline-specific data structures of each CRCs: For instance, CRC 1430 explores fundamental molecular mechanisms underlying cell state transitions using a broad variety of lab experiments as well as microscopy imaging techniques [1], while CRC/TRR 296 LOCOTACT investigates local control of thyroid hormone action in physiology and pathophysiology with a strong focus on OMICS data. CRC/TRR 196 MARIE, on the other hand, develops mobile material characterization systems, enabling the mapping of materials in dynamic environments and producing highly relevant data collections for the terahertz community [2], [3]. As a result, a standardized portfolio of RDM tools has been defined and implemented, comprising a cloud service (Nextcloud) for convenient data sharing, a repository (Dataverse) for sophisticated data registering and interlinking, an electronic lab notebook (eLabFTW) for extensive process documentation and OMERO for maintaining imaging data. These tools were evaluated [4] and piloted in the CRCs, with adaptations made to subject- and method-specific workflows and relevant metadata [5]. Last but not least, a strategic design decision had to be made by RDS when selecting the RDM tools, with a focus on long-term operability and connectivity. The tools were subsequently opened up to other researchers and scaled for university-wide use, spreading CRC's best practice into the research community. The introduction as well as the on-going usage of all tools have been accompanied by a comprehensive training program developed in cooperation with the three INF projects, which is now offered permanently as part of the "RDM Curriculum" [6]. A crucial component of the established link between projects and central services is an institutionalized data steward network comprising data stewards from projects and the RDS team, which facilitates the exchange of experiences and materials, discussion of requests, further development of RDM concepts, and planning of joint training courses and events. The centralized approach at UDE has several benefits: - Discipline-specific support: The standardized portfolio of RDM tools allows for subject- and method-specific workflows in the CRCs, ensuring effective support for diverse research needs. - Knowledge transfer and continuity: The data steward network enables the exchange of experience and knowledge between data stewards and central RDM staff, ensuring the continuity of expertise. - Synergies and efficiency: By reusing and adapting existing RDM tools and concepts, researchers can benefit from synergies between different projects, reducing the need for redundant training and tool development. - University-wide accessibility: The RDM tools are scaled for university-wide use, providing researchers across the institution with access to essential RDM services. In conclusion, UDE's centralized approach to RDM services has successfully balanced generic and discipline-specific needs, providing a sustainable and customizable infrastructure for research data management for single researchers as well as CRCs.